Pan-specific prediction of peptide-MHC Class I complex stability, a correlate of T cell immunogenicity
- Autores
- Rasmussen, Michael; Fenoy, Luis Emilio; Harndahl, Mikkel; Kristensen, Anne Bregnballe; Nielsen, Ida Kallehauge; Nielsen, Morten; Buus, Søren
- Año de publicación
- 2016
- Idioma
- inglés
- Tipo de recurso
- artículo
- Estado
- versión publicada
- Descripción
- Binding of peptides to MHC class I (MHC-I) molecules is the most selective event in the processing and presentation of Ags to CTL, and insights into the mechanisms that govern peptide-MHC-I binding should facilitate our understanding of CTL biology. Peptide-MHC-I interactions have traditionally been quantified by the strength of the interaction, that is, the binding affinity, yet it has been shown that the stability of the peptide-MHC-I complex is a better correlate of immunogenicity compared with binding affinity. In this study, we have experimentally analyzed peptide-MHC-I complex stability of a large panel of human MHC-I allotypes and generated a body of data sufficient to develop a neural network-based pan-specific predictor of peptide-MHC-I complex stability. Integrating the neural network predictors of peptide-MHC-I complex stability with state-of-the-art predictors of peptide-MHC-I binding is shown to significantly improve the prediction of CTL epitopes. The method is publicly available at http://www.cbs.dtu.dk/services/NetMHCstabpan.
Fil: Rasmussen, Michael. Universidad de Copenhagen; Dinamarca
Fil: Fenoy, Luis Emilio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones Biotecnológicas. Instituto de Investigaciones Biotecnológicas ; Argentina
Fil: Harndahl, Mikkel. Universidad de Copenhagen; Dinamarca
Fil: Kristensen, Anne Bregnballe. Universidad de Copenhagen; Dinamarca
Fil: Nielsen, Ida Kallehauge. Universidad de Copenhagen; Dinamarca
Fil: Nielsen, Morten. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de Copenhagen; Dinamarca
Fil: Buus, Søren. Universidad de Copenhagen; Dinamarca - Materia
-
Mhc-I
Stability
Predictor
Immunology - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
- Repositorio
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/49514
Ver los metadatos del registro completo
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network_name_str |
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Pan-specific prediction of peptide-MHC Class I complex stability, a correlate of T cell immunogenicityRasmussen, MichaelFenoy, Luis EmilioHarndahl, MikkelKristensen, Anne BregnballeNielsen, Ida KallehaugeNielsen, MortenBuus, SørenMhc-IStabilityPredictorImmunologyhttps://purl.org/becyt/ford/1.2https://purl.org/becyt/ford/1Binding of peptides to MHC class I (MHC-I) molecules is the most selective event in the processing and presentation of Ags to CTL, and insights into the mechanisms that govern peptide-MHC-I binding should facilitate our understanding of CTL biology. Peptide-MHC-I interactions have traditionally been quantified by the strength of the interaction, that is, the binding affinity, yet it has been shown that the stability of the peptide-MHC-I complex is a better correlate of immunogenicity compared with binding affinity. In this study, we have experimentally analyzed peptide-MHC-I complex stability of a large panel of human MHC-I allotypes and generated a body of data sufficient to develop a neural network-based pan-specific predictor of peptide-MHC-I complex stability. Integrating the neural network predictors of peptide-MHC-I complex stability with state-of-the-art predictors of peptide-MHC-I binding is shown to significantly improve the prediction of CTL epitopes. The method is publicly available at http://www.cbs.dtu.dk/services/NetMHCstabpan.Fil: Rasmussen, Michael. Universidad de Copenhagen; DinamarcaFil: Fenoy, Luis Emilio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones Biotecnológicas. Instituto de Investigaciones Biotecnológicas ; ArgentinaFil: Harndahl, Mikkel. Universidad de Copenhagen; DinamarcaFil: Kristensen, Anne Bregnballe. Universidad de Copenhagen; DinamarcaFil: Nielsen, Ida Kallehauge. Universidad de Copenhagen; DinamarcaFil: Nielsen, Morten. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de Copenhagen; DinamarcaFil: Buus, Søren. Universidad de Copenhagen; DinamarcaAmerican Association of Immunologists2016-07info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/49514Rasmussen, Michael; Fenoy, Luis Emilio; Harndahl, Mikkel; Kristensen, Anne Bregnballe; Nielsen, Ida Kallehauge; et al.; Pan-specific prediction of peptide-MHC Class I complex stability, a correlate of T cell immunogenicity; American Association of Immunologists; Journal of Immunology; 197; 4; 7-2016; 1517-15240022-1767CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.4049/jimmunol.1600582info:eu-repo/semantics/altIdentifier/url/http://www.jimmunol.org/content/197/4/1517info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-15T15:26:13Zoai:ri.conicet.gov.ar:11336/49514instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-10-15 15:26:13.314CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse |
dc.title.none.fl_str_mv |
Pan-specific prediction of peptide-MHC Class I complex stability, a correlate of T cell immunogenicity |
title |
Pan-specific prediction of peptide-MHC Class I complex stability, a correlate of T cell immunogenicity |
spellingShingle |
Pan-specific prediction of peptide-MHC Class I complex stability, a correlate of T cell immunogenicity Rasmussen, Michael Mhc-I Stability Predictor Immunology |
title_short |
Pan-specific prediction of peptide-MHC Class I complex stability, a correlate of T cell immunogenicity |
title_full |
Pan-specific prediction of peptide-MHC Class I complex stability, a correlate of T cell immunogenicity |
title_fullStr |
Pan-specific prediction of peptide-MHC Class I complex stability, a correlate of T cell immunogenicity |
title_full_unstemmed |
Pan-specific prediction of peptide-MHC Class I complex stability, a correlate of T cell immunogenicity |
title_sort |
Pan-specific prediction of peptide-MHC Class I complex stability, a correlate of T cell immunogenicity |
dc.creator.none.fl_str_mv |
Rasmussen, Michael Fenoy, Luis Emilio Harndahl, Mikkel Kristensen, Anne Bregnballe Nielsen, Ida Kallehauge Nielsen, Morten Buus, Søren |
author |
Rasmussen, Michael |
author_facet |
Rasmussen, Michael Fenoy, Luis Emilio Harndahl, Mikkel Kristensen, Anne Bregnballe Nielsen, Ida Kallehauge Nielsen, Morten Buus, Søren |
author_role |
author |
author2 |
Fenoy, Luis Emilio Harndahl, Mikkel Kristensen, Anne Bregnballe Nielsen, Ida Kallehauge Nielsen, Morten Buus, Søren |
author2_role |
author author author author author author |
dc.subject.none.fl_str_mv |
Mhc-I Stability Predictor Immunology |
topic |
Mhc-I Stability Predictor Immunology |
purl_subject.fl_str_mv |
https://purl.org/becyt/ford/1.2 https://purl.org/becyt/ford/1 |
dc.description.none.fl_txt_mv |
Binding of peptides to MHC class I (MHC-I) molecules is the most selective event in the processing and presentation of Ags to CTL, and insights into the mechanisms that govern peptide-MHC-I binding should facilitate our understanding of CTL biology. Peptide-MHC-I interactions have traditionally been quantified by the strength of the interaction, that is, the binding affinity, yet it has been shown that the stability of the peptide-MHC-I complex is a better correlate of immunogenicity compared with binding affinity. In this study, we have experimentally analyzed peptide-MHC-I complex stability of a large panel of human MHC-I allotypes and generated a body of data sufficient to develop a neural network-based pan-specific predictor of peptide-MHC-I complex stability. Integrating the neural network predictors of peptide-MHC-I complex stability with state-of-the-art predictors of peptide-MHC-I binding is shown to significantly improve the prediction of CTL epitopes. The method is publicly available at http://www.cbs.dtu.dk/services/NetMHCstabpan. Fil: Rasmussen, Michael. Universidad de Copenhagen; Dinamarca Fil: Fenoy, Luis Emilio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones Biotecnológicas. Instituto de Investigaciones Biotecnológicas ; Argentina Fil: Harndahl, Mikkel. Universidad de Copenhagen; Dinamarca Fil: Kristensen, Anne Bregnballe. Universidad de Copenhagen; Dinamarca Fil: Nielsen, Ida Kallehauge. Universidad de Copenhagen; Dinamarca Fil: Nielsen, Morten. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de Copenhagen; Dinamarca Fil: Buus, Søren. Universidad de Copenhagen; Dinamarca |
description |
Binding of peptides to MHC class I (MHC-I) molecules is the most selective event in the processing and presentation of Ags to CTL, and insights into the mechanisms that govern peptide-MHC-I binding should facilitate our understanding of CTL biology. Peptide-MHC-I interactions have traditionally been quantified by the strength of the interaction, that is, the binding affinity, yet it has been shown that the stability of the peptide-MHC-I complex is a better correlate of immunogenicity compared with binding affinity. In this study, we have experimentally analyzed peptide-MHC-I complex stability of a large panel of human MHC-I allotypes and generated a body of data sufficient to develop a neural network-based pan-specific predictor of peptide-MHC-I complex stability. Integrating the neural network predictors of peptide-MHC-I complex stability with state-of-the-art predictors of peptide-MHC-I binding is shown to significantly improve the prediction of CTL epitopes. The method is publicly available at http://www.cbs.dtu.dk/services/NetMHCstabpan. |
publishDate |
2016 |
dc.date.none.fl_str_mv |
2016-07 |
dc.type.none.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion http://purl.org/coar/resource_type/c_6501 info:ar-repo/semantics/articulo |
format |
article |
status_str |
publishedVersion |
dc.identifier.none.fl_str_mv |
http://hdl.handle.net/11336/49514 Rasmussen, Michael; Fenoy, Luis Emilio; Harndahl, Mikkel; Kristensen, Anne Bregnballe; Nielsen, Ida Kallehauge; et al.; Pan-specific prediction of peptide-MHC Class I complex stability, a correlate of T cell immunogenicity; American Association of Immunologists; Journal of Immunology; 197; 4; 7-2016; 1517-1524 0022-1767 CONICET Digital CONICET |
url |
http://hdl.handle.net/11336/49514 |
identifier_str_mv |
Rasmussen, Michael; Fenoy, Luis Emilio; Harndahl, Mikkel; Kristensen, Anne Bregnballe; Nielsen, Ida Kallehauge; et al.; Pan-specific prediction of peptide-MHC Class I complex stability, a correlate of T cell immunogenicity; American Association of Immunologists; Journal of Immunology; 197; 4; 7-2016; 1517-1524 0022-1767 CONICET Digital CONICET |
dc.language.none.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
info:eu-repo/semantics/altIdentifier/doi/10.4049/jimmunol.1600582 info:eu-repo/semantics/altIdentifier/url/http://www.jimmunol.org/content/197/4/1517 |
dc.rights.none.fl_str_mv |
info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by-nc-sa/2.5/ar/ |
eu_rights_str_mv |
openAccess |
rights_invalid_str_mv |
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/ |
dc.format.none.fl_str_mv |
application/pdf application/pdf application/pdf |
dc.publisher.none.fl_str_mv |
American Association of Immunologists |
publisher.none.fl_str_mv |
American Association of Immunologists |
dc.source.none.fl_str_mv |
reponame:CONICET Digital (CONICET) instname:Consejo Nacional de Investigaciones Científicas y Técnicas |
reponame_str |
CONICET Digital (CONICET) |
collection |
CONICET Digital (CONICET) |
instname_str |
Consejo Nacional de Investigaciones Científicas y Técnicas |
repository.name.fl_str_mv |
CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas |
repository.mail.fl_str_mv |
dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar |
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1846083405757808640 |
score |
13.22299 |